Cognitive Dysfunction Among Adults With Type 2 Diabetes Mellitus in Karnataka, India
Bibliographic record
Abstract
Background: Type 2 diabetes mellitus is a chronic metabolic disease characterized by hyperglycemia that affects various body systems. Elevated blood glucose levels cause brain malfunction, sorbitol-induced blood vessel damage, and degeneration of the nerves that can lead to dementia or cognitive impairment. Cognitive impairment can result in nonadherence of patients to diabetes treatment, such as diet, medication, and exercise. Methods: We used a cross-sectional design to individually interview 194 patients with type 2 diabetes in a rural field practice area in India. A questionnaire was used to collect sociodemographic and diabetes disease characteristics; anthropometric measurements were also collected. Cognitive dysfunction was assessed with the Kannada version (local language) of the Montreal Cognitive Assessment (MoCA) tool. Blood pressure was measured for all subjects using a standardized sphygmomanometer on the right arm with the patient in a sitting position. Results: Among the 194 diabetic subjects interviewed, 98 (50.5%) were cognitively impaired. More than half of the subjects (56.2%) were 65 years, and female participants (53.6%) outnumbered males (46.4%). The majority of patients (62.4%) had had diabetes for <10 years. The sociodemographic characteristics age, sex, education, occupation, and socioeconomic status and the anthropometric measurement of waist-to-hip ratio were significantly associated (P<0.05) with cognitive impairment. Disease characteristics, religion, and blood pressure showed no significant association with cognitive impairment. Conclusion: One in two individuals with type 2 diabetes mellitus in our study population had mild cognitive impairment. Older individuals in the low socioeconomic strata and with low levels of education were identified to be at high risk of cognitive impairment. Hence, screening and appropriate care need to be provided.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".